Enhancing reaction-based de novo design using a multi-label reaction class recommender.

Reaction-based de novo design refers to the in-silico generation of novel chemical structures by combining reagents using structural transformations derived from known reactions. The driver for using reaction-based transformations is to increase the likelihood of the designed molecules being synthetically accessible. We have previously described a reaction-based de novo design method based on reaction vectors which are transformation rules that are encoded automatically from reaction databases. A limitation of reaction vectors is that they account for structural changes that occur at the core of a reaction only, and they do not consider the presence of competing functionalities that can compromise the reaction outcome. Here, we present the development of a Reaction Class Recommender to enhance the reaction vector framework. The recommender is intended to be used as a filter on the reaction vectors that are applied during de novo design to reduce the combinatorial explosion of in-silico molecules produced while limiting the generated structures to those which are most likely to be synthesisable. The recommender has been validated using an external data set extracted from the recent medicinal chemistry literature and in two simulated de novo design experiments. Results suggest that the use of the recommender drastically reduces the number of solutions explored by the algorithm while preserving the chance of finding relevant solutions and increasing the global synthetic accessibility of the designed molecules.

A cross-industry forum on benchmarking critical quality attribute identification and linkage to process characterization studies.

Identification of Critical Quality Attributes (CQAs) and subsequent characterization in process development studies are the key elements of quality by design (QbD) for biopharmaceutical products. Since the inception of ICH Q8R2, several articles have been published on approaches to conducting CQA risk assessments as well as the application to process understanding. A survey was conducted by multiple companies participating in an International Consortium working group on the best practices for identifying CQAs with linkages to process characterization (PC) studies. The results indicate that the companies surveyed are using similar approaches/timing to identify CQAs during process development. Consensus was also observed among the companies surveyed with approaches to linkage of CQAs to process characterization studies leading to impact to control strategies and lifecycle management.

Regulatory assessment of drug dissolution profiles comparability via maximum deviation.

In drug development, comparability of dissolution profiles of 2 different formulations is usually assessed using the similarity factor f2 . In practice, the drug dissolution profiles are deemed similar if the f2 exceeds 50, which occurs when a 10% maximum difference in the mean percentage of the dissolved drug at each time point between test and reference formulation is obtained. According to the Guideline on the Investigation of Bioequivalence (CPMP/EWP/QWP/1401/98 Rev. 1/ Corr **) use of the f2 is however restricted by a set of validity conditions. If some of these conditions are not satisfied, the f2 is not considered suitable, and alternative statistical methods are needed. In this article, we propose an inferential framework based on the maximum deviation between curves to test the comparability of drug dissolution profiles. The new methodology is applicable regardless whether the validity criteria of the f2 are met or not. Contrary to the f2 , this approach also integrates the variability of the measurements over time and not only their average. To benchmark our method, we performed simulations informed by 3 real case studies provided by the European Medicines Agency and extracted from dossiers submitted to the Centralised Procedure for Marketing Authorisation Application. In the scenarios of the simulation study, the new method controlled its type I error rate when the maximum deviation was greater than the similarity acceptance limit of 10%. The power exceeded 80% for small values of the maximum deviation, while the test was more conservative for intermediate ones. Our results were also very robust to sampling variations. Based on these positive findings, we encourage applicants to consider the new maximum deviation-based method as a valid alternative to the f2 , especially when the validity criteria of the latter are not met.

Comparison of Dissolution Similarity Assessment Methods for Products with Large Variations: f2 Statistics and Model-Independent Multivariate Confidence Region Procedure for Dissolution Profiles of Multiple Oral Products.

The current Japanese Ministry of Health Labour and Welfare (MHLW)'s Guideline for Bioequivalence Studies of Generic Products uses averaged dissolution rates for the assessment of dissolution similarity between test and reference formulations. This study clarifies how the application of model-independent multivariate confidence region procedure (Method B), described in the European Medical Agency and U.S. Food and Drug Administration guidelines, affects similarity outcomes obtained empirically from dissolution profiles with large variations in individual dissolution rates. Sixty-one datasets of dissolution profiles for immediate release, oral generic, and corresponding innovator products that showed large variation in individual dissolution rates in generic products were assessed on their similarity by using the f2 statistics defined in the MHLW guidelines (MHLW f2 method) and two different Method B procedures, including a bootstrap method applied with f2 statistics (BS method) and a multivariate analysis method using the Mahalanobis distance (MV method). The MHLW f2 and BS methods provided similar dissolution similarities between reference and generic products. Although a small difference in the similarity assessment may be due to the decrease in the lower confidence interval for expected f2 values derived from the large variation in individual dissolution rates, the MV method provided results different from those obtained through MHLW f2 and BS methods. Analysis of actual dissolution data for products with large individual variations would provide valuable information towards an enhanced understanding of these methods and their possible incorporation in the MHLW guidelines.

The impact of data integrity on decision making in early lead discovery.

Data driven decision making is a key element of today's pharmaceutical research, including early drug discovery. It comprises questions like which target to pursue, which chemical series to pursue, which compound to make next, or which compound to select for advanced profiling and promotion to pre-clinical development. In the following paper we will exemplify how data integrity, i.e. the context data is generated in and auxiliary information that is provided for individual result records, can influence decision making in early lead discovery programs. In addition we will describe some approaches which we pursue at Boehringer Ingelheim to reduce the risk for getting misguided.

More than just crushing: a prospective pre-post intervention study to reduce drug preparation errors in patients with feeding tubes.

WHAT IS KNOWN AND OBJECTIVES: Incorrect drug preparation for patients with feeding tubes can result in harm for the patient and the preparing person. Combined intervention programs are effective tools to reduce such preparation errors. However, to date, intervention programs have been mostly tested in hospitals with computerized physician order entry (CPOE), unit-dose systems, or ward-based clinical pharmacists. Hence, the primary objective of this study was to develop and evaluate an intervention program tailored to hospitals without such preconditions. METHODS: We conducted a prospective pre-/post-intervention study on a gastroenterological intensive care unit (ICU) and a surgical ward for oral, dental and maxillofacial diseases (surgical ward). During the study periods, observers documented and evaluated drug preparation processes of all peroral drugs for patients with feeding tubes. The primary endpoint was the rate of inappropriately crushed and/or suspended solid peroral drugs in regards to all solid peroral drugs. RESULTS AND DISCUSSION: Altogether, we evaluated 775 drug preparation processes of solid peroral drugs on the ICU and 975 on the surgical ward. The intervention program significantly reduced incorrect crushing and/or suspending of solid peroral drugs for administration to patients with feeding tubes from 9·8% to 4·2% (P < 0·01) on the ICU and from 5·7% to 1·4% (P < 0·01) on the surgical ward. WHAT IS NEW AND CONCLUSION: The implementation of the newly developed intervention program significantly reduced the rate of inappropriately prepared solid peroral drugs, suggesting that it is an effective measure to enable safe drug administration for inpatients with feeding tubes.

Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening.

Analyzing the chemical space coverage in commercial fragment screening collections revealed the overlap between bioactive medicinal chemistry substructures and rule-of-three compliant fragments is only ∼25%. We recommend including these fragments in fragment screening libraries to maximize confidence in discovering hit matter within known bioactive chemical space, while incorporation of nonoverlapping substructures could offer novel hits in screening libraries. Using principal component analysis, polar and three-dimensional substructures display a higher-than-average enrichment of bioactive compounds, indicating increasing representation of these substructures may be beneficial in fragment screening.

[Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

The use of ethanol in paediatric formulations in New Zealand.

UNLABELLED: Children's right to access safe and effective medicines is recognised globally. Ethanol, used in paediatric liquid formulations as a solvent and preservative, is associated with safety concerns with respect to both acute ingestion and chronic exposure. In addition, families may have cultural or religious values making ethanol use inappropriate when alternatives are available. International guidelines aim to reduce, and if possible eliminate, the use of ethanol in paediatric medicines. Guidelines on labelling vary globally, limiting the ability of health professionals and patients to make informed decisions on appropriate medicines. This study aimed to explore the availability of ethanol-containing medicines for use in the paediatric population in New Zealand and to discuss findings alongside international guidelines. Forty-seven paediatric liquid medicines were identified containing ethanol. The ethanol concentration could be determined in 35 of these medicines and ranged from 0.6 % v/v to an alarming 76 % v/v ethanol. If recommended dosing instructions are followed, the ethanol consumed per dose is not expected to cause acute toxic effects. The medicines identified are indicated for both acute and chronic use, including digoxin (10.1-11.4 % v/v ethanol) which is used in patients of all ages, including preterm neonates. CONCLUSION: Stronger guidance should be provided to reduce the use of ethanol in paediatric medicines, in New Zealand and globally. If ethanol is used, full disclosure of its presence and concentration on the product label is essential to enable prescribers and patients to make informed decisions on the most suitable pharmaceutical formulations.

Evaluation of the impacts of formulation variables and excipients on the drug release dynamics of a polyamide 6,10-based monolithic matrix using mathematical tools.

Drug release from hydrophilic matrices is regulated mainly by polymeric erosion, disentanglement, dissolution, swelling front movement, drug dissolution and diffusion through the polymeric matrix. These processes depend upon the interaction between the dissolution media, polymeric matrix and drug molecules, which can be significantly influenced by formulation variables and excipients. This study utilized mathematical parameters to evaluate the impacts of selected formulation variables and various excipients on the release performance of hydrophilic polyamide 6,10 (PA 6,10) monolithic matrix. Amitriptyline HCl and theophylline were employed as the high and low solubility model drugs, respectively. The incorporation of different excipient concentrations and changes in formulation components influenced the drug release dynamics as evidenced by computed mathematical quantities (t x%, MDT x%, f 1, f 2, k 1, k 2, and К F). The effects of excipients on drug release from the PA 6,10 monolithic matrix was further elucidated using static lattice atomistic simulations wherein the component energy refinements corroborates the in vitro and in silico experimental data. Consequently, the feasibility of modulating release kinetics of drug molecules from the novel PA 6,10 monolithic matrix was well suggested.

Solubility-modulated asymmetric membrane tablets of triprolidine hydrochloride: statistical optimization and evaluation.

The aim of the present study was to develop asymmetric membrane (AM) tablets for controlled delivery of highly water-soluble antihistaminic drug triprolidine hydrochloride. The solubility of triprolidine hydrochloride was modulated through the incorporation of coated sodium chloride crystals encapsulated with asymmetric membrane coating polymer, cellulose acetate butyrate. Formulation of AM tablets was based on a 2(3) factorial design to study the effect of formulation variables, namely, polymer concentration, level of pore former, and amount of osmogen on the in vitro release. Core tablets prepared by wet granulation and coated with asymmetric membrane by a dip coating method were evaluated. Statistical analysis was done with the Design Expert Software 8.0.2 (USA), and the polynomial equation generated by Pareto charts was used for validation of the experimental design. The interaction chart and response surface plots deduced the simultaneous effect of independent variables on in vitro drug release. The in vitro drug release was inversely proportional and directly related to the level(s) of polymer and pore former in the membrane, respectively. The level of osmogen not only increased the osmotic pressure but also controlled the drug release due to a common ion effect. The drug release of the optimized formulation (F6) followed zero-order kinetics, which would be capable of reducing the administration, and was stable over 3 months. SEM photographs revealed asymmetry in membrane structure.

[Cluster analysis on authorized patents of compound traditional Chinese medicines with different efficacy in 2010].

OBJECTIVE: To discuss the authorized patent of compound traditional Chinese medicines with different efficacy in 2010, in order to provide reference for R&D of relevant compounds and patent protection. METHOD: Literatures for patents of compound traditional Chinese medicines were searched to screen relevant data and create a sample space. The samples were classified by hierarchical cluster procedures and iterative partitioning procedures using "authorized percentage" and "authorized time interval" as variable quantities. The comprehensive results generated by the two clustering methods were used to draw a conclusion. RESULT: The samples were classified into four groups by clustering methods, each has significant difference in authorized patents' number and authorized time interval with others. CONCLUSION: Among compounds showing therapeutic advantage of traditional Chinese medicines, patents with short authorization period and in less number can be given most attention for patent application. Those with longer authorization period and in less number can be given more attention. While those with shorter authorization period and in large number can also be given attention for information guidance for traditional Chinese medicine science and technology and commercialization of patent achievements.

[Current service invention patents and growth pathways on basis of cluster analysis].

This study aims for enhancing quantity and quality of patents of traditional Chinese medicine compounds of traditional Chinese medicine enterprises, traditional Chinese medicine colleges and relevant institutions while building an efficient pathway for patent protection using simple statistics and cluster analysis, with service invention patent holders of traditional Chinese medicine compounds as the study object.

Validation and application of RP-HPLC method for the quantification of metoclopramide hydrochloride in oral formulations prepared for IVIVC studies.

The objective of this study is to develop sensitive and cost effective reverse phase high performance liquid chromatographic method for the estimation of Metoclopramide Hydrochloride in oral solid dosage formulations. A reverse chromatographic method was used with the mobile phase of Acetonitrile, 20m M Potassium dihydrogen phosphate buffer solution (pH 3 adjusted with orthophosphoric acid) in the ratio of 40:60. The column used was Waters C18 3.9×300mm µBondapak (RP). The flow rate of the mobile phase was 2ml/minute. The detector was set at the wavelength of 275nm.This method showed good sensitivity. The linearity was also found to be excellent (γ(2)=0.997) in the range of 5-75 µg/ml. No interfering peaks were observed at the retention time of Metoclopramide Hydrochloride when both placebo and blank samples were injected (Retention time =1.93min). The parameters such as specificity, linearity, range, accuracy, precision, system suitability, solution stability, detection and quantification limits were evaluated to validate this method. This method can effectively be used for quantitative analysis of Metoclopramide hydrochloride tablet formulations because of its specificity, accuracy and convenience of use.

Effects of aerosol formulation to amino acids and fatty acids contents in Haruan extract.

Haruan (Channa striatus) extract was formulated to aerosol for wound and burn treatment. Haruan extract is containing amino acids and fatty acids that important for wound healing process. The purpose of this study is to observe the effect of formulation and other excipients in the formula to amino acids and fatty acids content in Haruan extract before and after formulated into aerosol. Precolumn derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) method is used for amino acids analysis. Fatty acids in Haruan extract were esterified using transesterification method to form FAMEs before analyzed using GC. Boron trifluoride-methanol reagent is used for transesterification. Tyrosine and methionine concentrations were different after formulated. The concentrations were decrease. There are six fatty acids have amount that significantly different after formulated into concentrate and aerosol. Contents of these fatty acids were increase. Generally, fatty acids which had content increased after formulated were the long-chain fatty acids. This might be happen because of chain extension process. Saponification and decarboxylation would give the chain extended product. Therefore contents of long-chain fatty acids were increase. Generally, the aerosol formulation did not affect the amino acids concentrations in Haruan extract while some long-chain fatty acids concentrations were increase after formulated into concentrate and aerosol.

Development and stability evaluation of enteric coated Diclofenac sodium tablets using Sureteric.

This study was aimed to develop a stable enteric coated diclofenac sodium tablets using Sureteic without a subcoating layer. Diclofenac uncoated tablets were developed and manufactured through the non direct compression process. Sureteric white aqueous coating dispersion was used as enteric coating material. Sureteric is a special mixture of Polyvinyl Acetate Phthalate (Phthalavin (R), PVAP), plasticizers and other ingredients in a suitable optimized dry powder formulation. The obtained enteric coated tablets were subjected to disintegration and no sign of cracking was observed when they placed in a hydrochloric solution at pH 1.2, but they were completely disintegrated within 10 minutes when they putted in buffered solution at pH6.8. Dissolution test was also conducted by placing tablets in 0.1 M HCl for 2 hours and then 1 hour in phosphate buffer at pH 6.8. Less than 0.9% of drug was released in the acidic phase and up to 97% in the basic medium. These results show that Sureteric can be successfully used to produce diclofenac sodium enteric coated tablets in order to prevent its release in the stomach and facilitate immediate release of the drug in the duodenum. These findings suggest that aqueous enteric coating with Sureteric system is an easy and economical approach for preparing stable diclofenac sodium enteric coat without the use of a subcoating layer.

Accelerating chemical database searching using graphics processing units.

The utility of chemoinformatics systems depends on the accurate computer representation and efficient manipulation of chemical compounds. In such systems, a small molecule is often digitized as a large fingerprint vector, where each element indicates the presence/absence or the number of occurrences of a particular structural feature. Since in theory the number of unique features can be exceedingly large, these fingerprint vectors are usually folded into much shorter ones using hashing and modulo operations, allowing fast "in-memory" manipulation and comparison of molecules. There is increasing evidence that lossless fingerprints can substantially improve retrieval performance in chemical database searching (substructure or similarity), which have led to the development of several lossless fingerprint compression algorithms. However, any gains in storage and retrieval afforded by compression need to be weighed against the extra computational burden required for decompression before these fingerprints can be compared. Here we demonstrate that graphics processing units (GPU) can greatly alleviate this problem, enabling the practical application of lossless fingerprints on large databases. More specifically, we show that, with the help of a ~$500 ordinary video card, the entire PubChem database of ~32 million compounds can be searched in ~0.2-2 s on average, which is 2 orders of magnitude faster than a conventional CPU. If multiple query patterns are processed in batch, the speedup is even more dramatic (less than 0.02-0.2 s/query for 1000 queries). In the present study, we use the Elias gamma compression algorithm, which results in a compression ratio as high as 0.097.

Normalizing molecular docking rankings using virtually generated decoys.

Drug discovery research often relies on the use of virtual screening via molecular docking to identify active hits in compound libraries. An area for improvement among many state-of-the-art docking methods is the accuracy of the scoring functions used to differentiate active from nonactive ligands. Many contemporary scoring functions are influenced by the physical properties of the docked molecule. This bias can cause molecules with certain physical properties to incorrectly score better than others. Since variation in physical properties is inevitable in large screening libraries, it is desirable to account for this bias. In this paper, we present a method of normalizing docking scores using virtually generated decoy sets with matched physical properties. First, our method generates a set of property-matched decoys for every molecule in the screening library. Each library molecule and its decoy set are docked using a state-of-the-art method, producing a set of raw docking scores. Next, the raw docking score of each library molecule is normalized against the scores of its decoys. The normalized score represents the probability that the raw docking score was drawn from the background distribution of nonactive property-matched decoys. Assuming that the distribution of scores of active molecules differs from the nonactive score distribution, we expect that the score of an active compound will have a low probability of having been drawn from the nonactive score distribution. In addition to the use of decoys in normalizing docking scores, we suggest that decoy sets may be a useful tool to evaluate, improve, or develop scoring functions. We show that by analyzing docking scores of library molecules with respect to the docking scores of their virtually generated property-matched decoys, one can gain insight into the advantages, limitations, and reliability of scoring functions.

TRAVIS - a free analyzer and visualizer for Monte Carlo and molecular dynamics trajectories.

We present TRAVIS ("TRajectory Analyzer and VISualizer"), a free program package for analyzing and visualizing Monte Carlo and molecular dynamics trajectories. The aim of TRAVIS is to collect as many analyses as possible in one program, creating a powerful tool and making it unnecessary to use many different programs for evaluating simulations. This should greatly rationalize and simplify the workflow of analyzing trajectories. TRAVIS is written in C++, open-source freeware and licensed under the terms of the GNU General Public License (GPLv3). It is easy to install (platform independent, no external libraries) and easy to use. In this article, we present some of the algorithms that are implemented in TRAVIS - many of them widely known for a long time, but some of them also to appear in literature for the first time. All shown analyses only require a standard MD trajectory as input data.

Predicting pK(a) values of substituted phenols from atomic charges: comparison of different quantum mechanical methods and charge distribution schemes.

The acid dissociation (ionization) constant pK(a) is one of the fundamental properties of organic molecules. We have evaluated different computational strategies and models to predict the pK(a) values of substituted phenols using partial atomic charges. Partial atomic charges for 124 phenol molecules were calculated using 83 approaches containing seven theory levels (MP2, HF, B3LYP, BLYP, BP86, AM1, and PM3), three basis sets (6-31G*, 6-311G, STO-3G), and five population analyses (MPA, NPA, Hirshfeld, MK, and Löwdin). The correlations between pK(a) and various atomic charge descriptors were examined, and the best descriptors were selected for preparing the quantitative structure-property relationship (QSPR) models. One QSPR model was created for each of the 83 approaches to charge calculation, and then the accuracy of all these models was analyzed and compared. The pK(a)s predicted by most of the models correlate strongly with experimental pK(a) values. For example, more than 25% of the models have correlation coefficients (R²) greater than 0.95 and root-mean-square errors smaller than 0.49. All seven examined theory levels are applicable for pK(a) prediction from charges. The best results were obtained for the MP2 and HF level of theory. The most suitable basis set was found to be 6-31G*. The 6-311G basis set provided slightly weaker correlations, and unexpectedly also, the STO-3G basis set is applicable for the QSPR modeling of pK(a). The Mulliken, natural, and Löwdin population analyses provide accurate models for all tested theory levels and basis sets. The results provided by the Hirshfeld population analysis were also acceptable, but the QSPR models based on MK charges show only weak correlations.